ENIGMA- Addiction: Pooling of Existing Datasets to Identify Brain and Genetic Correlates of Addiction

项目总结 谜团(http://enigma.ini.usc.edu/))的成立是为了研究大脑的结构、功能、 通过将来自多个地点的基因组和神经成像数据结合在一起来研究和诊断疾病。它的目标是最大化地 统计能力和现有数据集的收益，通过非常大的数据池努力。这个目标有 鉴于对许多神经成像和成像的严密性和重复性的担忧，今天增加了重要性 基因组研究结果。自从它最初的成功(一项全基因组的皮质下体积与 超过26,000名参与者，Stein等人，2012自然遗传学)，一些工作组已经 建立了利用标准化的多点谜前处理流水线和分析方法 研究特定疾病的神经生物学。此应用程序的PI创建了正在工作的谜上瘾 该小组现在可以访问代表14000多名参与者的数据集。基因组和神经成像 对这一史无前例的数据收集的分析应该会对神经产生重要的新见解 以及成瘾的遗传基础。基于我们最初的概念验证资金(R21DA038381)，我们建议 为了进一步扩大目前只包括世界上一小部分人的成瘾工作组 潜在的相关数据集，以确定用于遗传关联分析的健壮的大脑依赖标记， 并检查不同物质使用阶段之间转换的遗传和大脑标记 寿命。我们还将增加大脑测量的范围，以包括结构和功能 连接(DTI和静息状态数据)，并将开发对大脑结构的形态测量分析。我们 可以使用这些生物标记物来评估大脑变化是在依赖之前还是在早期或 如果这些影响通过利用家族性的、发育性的、 我们工作组中的纵向和禁欲样本。我们将创建一个数据分析门户， 提供对池化数据的广泛访问和优化的分析方法，最大限度地提高严密性和 重复性(例如，适当的协变量、嵌套的方差模型、倾向加权 社会人口学、交叉验证)，从而指导其他人适当和明智地使用这些数据。 分析门户将对分析进行归档(例如，准确的主题和分析脚本)以确保最佳实践 和完全透明。我们将积极致力于扩大联合体，打造独一无二的大型 神经成像-遗传性成瘾数据集，我们将向研究社区免费提供结果 通过在线交互工具Enigma-Vis(http://enigma.ini.usc.edu/enigma-vis/).

PROJECT SUMMARY The ENIGMA consortium (http://enigma.ini.usc.edu/) was established to investigate brain structure, function, and disease by combining genomic and neuroimaging datasets from multiple sites. Its goal is to maximize statistical power and the yield from existing datasets through very large data pooling efforts. This goal has added importance today in light of concerns over the rigor and reproducibility of many neuroimaging and genomic findings. Since its initial successes (a genome wide association study on subcortical volumes with over 26,000 participants, Stein et al., 2012 Nature Genetics), a number of working groups have been established which use the standardized multi-site ENIGMA preprocessing pipelines and analytic methods to study the neurobiology of specific diseases. This application's PIs created the ENIGMA Addiction working group which now has access to datasets representing over 14000 participants. Genomic and neuromaging analyses on this unprecedented collection of data should produce important new insights into the neural and genetic basis of addiction. Building on our initial proof of concept funding (R21DA038381), we propose to further expand the Addiction working group which currently includes only a fraction of the world's potential relevant datasets, to identify robust brain markers of dependence for genetic association analyses, and to examine genetic and brain markers for the transition between stages of substance use across the lifespan. We will also increase the range of brain measures examined to include structural and functional connectivity (DTI and resting-state data) and will develop morphometric analyses of brain structures. We can use these biomarkers to assess if brain alterations preceded dependence or arose during early or chronic use and if these effects correct with abstinence by exploiting the familial, developmental, longitudinal and abstinence samples in our working group. We will create a data analysis portal that will provide both wide access to the pooled data and optimized analytic methods that maximize rigor and reproducibility (e.g., appropriate covariates, nested variance models, propensity weighting for sociodemographics, cross-validation) thereby guiding others to use these data appropriately and wisely. The analysis portal will archive analyses (e.g., exact subjects and analysis scripts) to ensure best practice and full transparency. We will actively work to expand the consortium to create a uniquely large neuroimaging-genetic addiction dataset and we will make results freely available to the research community through the online interactive tool ENIGMA-Vis (http://enigma.ini.usc.edu/enigma-vis/).